Resource provisioning in collaborative fog computing for multiple delay‐sensitive users

2021 ◽  
Author(s):  
Shuaibing Lu ◽  
Jie Wu ◽  
Ning Wang ◽  
Yubin Duan ◽  
Haiming Liu ◽  
...  
Keyword(s):  
Fog Computing ◽  
Resource Provisioning ◽  
Multiple Delay ◽  
Delay Sensitive

scholarly journals Delay-Sensitive Task Offloading in the 802.11p-Based Vehicular Fog Computing Systems

2020 ◽  
Vol 7 (1) ◽  
pp. 773-785 ◽  
Author(s):  
Qiong Wu ◽  
Hanxu Liu ◽  
Ruhai Wang ◽  
Pingyi Fan ◽  
Qiang Fan ◽  
...  
Keyword(s):  
Fog Computing ◽  
Computing Systems ◽  
Delay Sensitive ◽  
Task Offloading

A Novel Resource Management Framework for Fog Computing by Using Machine Learning Algorithm

2020 ◽  
pp. 42-52
Author(s):  
Shanthi Thangam Manukumar ◽  
Vijayalakshmi Muthuswamy
Keyword(s):  
Machine Learning ◽  
Resource Management ◽  
Mobile Devices ◽  
Service Providers ◽  
Learning Algorithm ◽  
Fog Computing ◽  
Mobile Network ◽  
Resource Provisioning ◽  
Management Framework ◽  
Iot Devices

With the development of edge devices and mobile devices, the authenticated fast access for the networks is necessary and important. To make the edge and mobile devices smart, fast, and for the better quality of service (QoS), fog computing is an efficient way. Fog computing is providing the way for resource provisioning, service providers, high response time, and the best solution for mobile network traffic. In this chapter, the proposed method is for handling the fog resource management using efficient offloading mechanism. Offloading is done based on machine learning prediction technology and also by using the KNN algorithm to identify the nearest fog nodes to offload. The proposed method minimizes the energy consumption, latency and improves the QoS for edge devices, IoT devices, and mobile devices.

Resource Provisioning and Scheduling Techniques of IoT Based Applications in Fog Computing

2019 ◽  
Vol 2 (2) ◽  
pp. 57-70 ◽  
Author(s):  
Rajni Gupta
Keyword(s):  
Oil And Gas ◽  
Health Care Systems ◽  
Fog Computing ◽  
Fast Response ◽  
Resource Provisioning ◽  
Time Data ◽  
Computing Paradigm ◽  
Care Systems ◽  
Cloud Environments ◽  
Suitable Technique

Internet of Things (IoT) has emerged as a computing paradigm to develop smart applications such e-health care systems, smart city, smart waste management systems, etc. It contains a large number of different devices and heterogeneous networks, which make it difficult to provide secure and fast response to the end user. To provide the faster response services, there is a need to use the concept of Fog computing Recently, the use of fog computing is a rapidly increasing in many industries for the development of applications such as manufacturing, e-health, oil and gas, As more and more users have started to store/process their real-time data in Fog-based Cloud environments, resource provisioning and scheduling of IoT based applications becomes a key element of consideration for efficient execution of these applications. This article will help to select the most suitable technique for processing smart IoT based applications in Fog computing environments.

Towards cost-efficient resource provisioning with multiple mobile users in fog computing

2020 ◽  
Vol 146 ◽  
pp. 96-106
Author(s):  
Shuaibing Lu ◽  
Jie Wu ◽  
Yubin Duan ◽  
Ning Wang ◽  
Juan Fang
Keyword(s):  
Fog Computing ◽  
Resource Provisioning ◽  
Mobile Users ◽  
Efficient Resource ◽  
Cost Efficient

scholarly journals Internet of Things-Based Energy Efficiency Optimization Model in Fog Smart Cities

2021 ◽  
Vol 5 (2) ◽  
pp. 105
Author(s):  
Wasswa Shafik ◽  
S. Mojtaba Matinkhah ◽  
Mamman Nur Sanda ◽  
Fawad Shokoor
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Response Time ◽  
Smart Grids ◽  
Smart Cities ◽  
Fog Computing ◽  
The Internet ◽  
Delay Sensitive ◽  
Service Delay

In recent years, the IoT) Internet of Things (IoT) allows devices to connect to the Internet that has become a promising research area mainly due to the constant emerging of the dynamic improvement of technologies and their associated challenges. In an approach to solve these challenges, fog computing came to play since it closely manages IoT connectivity. Fog-Enabled Smart Cities (IoT-ESC) portrays equitable energy consumption of a 7% reduction from 18.2% renewable energy contribution, which extends resource computation as a great advantage. The initialization of IoT-Enabled Smart Grids including (FESC) like fog nodes in fog computing, reduced workload in Terminal Nodes services (TNs) that are the sensors and actuators of the Internet of Things (IoT) set up. This paper proposes an integrated energy-efficiency model computation about the response time and delays service minimization delay in FESC. The FESC gives an impression of an auspicious computing model for location, time, and delay-sensitive applications supporting vertically -isolated, service delay, sensitive solicitations by providing abundant, ascendable, and scattered figuring stowage and system associativity. We first reviewed the persisting challenges in the proposed state-of-the models and based on them. We introduce a new model to address mainly energy efficiency about response time and the service delays in IoT-ESC. The iFogsim simulated results demonstrated that the proposed model minimized service delay and reduced energy consumption during computation. We employed IoT-ESC to decide autonomously or semi-autonomously whether the computation is to be made on Fog nodes or its transfer to the cloud.

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